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This paper newly proposes a fast enhanced exemplar-based clustering (FEEC) method for incomplete EEG signal. The algorithm first compresses the potential exemplar list and reduces the pairwise similarity matrix. By processing the most complete data in the first stage, FEEC then extends the few incomplete data into the exemplar list. A new compressed similarity matrix will be constructed and the scale of this matrix is greatly reduced. Finally, FEEC optimizes the new target function by the enhanced <mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\" id=\"M1\"><mml:mi>\u03b1<\/mml:mi><\/mml:math>-expansion move method. On the other hand, due to the pairwise relationship, FEEC also improves the generalization of this algorithm. In contrast to other exemplar-based models, the performance of the proposed clustering algorithm is comprehensively verified by the experiments on two datasets.<\/jats:p>","DOI":"10.1155\/2020\/4147807","type":"journal-article","created":{"date-parts":[[2020,5,8]],"date-time":"2020-05-08T19:30:53Z","timestamp":1588966253000},"page":"1-11","source":"Crossref","is-referenced-by-count":2,"title":["Fast Enhanced Exemplar-Based Clustering for Incomplete EEG Signals"],"prefix":"10.1155","volume":"2020","author":[{"given":"Anqi","family":"Bi","sequence":"first","affiliation":[{"name":"School of Computer Science and Engineering, Changshu Institute of Technology, Changshu, Jiangsu, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wenhao","family":"Ying","sequence":"additional","affiliation":[{"name":"School of Computer Science and Engineering, Changshu Institute of Technology, Changshu, Jiangsu, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3566-6796","authenticated-orcid":true,"given":"Lu","family":"Zhao","sequence":"additional","affiliation":[{"name":"School of Computer Science and Engineering, Changshu Institute of Technology, Changshu, Jiangsu, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","reference":[{"key":"1","doi-asserted-by":"publisher","DOI":"10.1142\/s0218194018500390"},{"key":"2","doi-asserted-by":"publisher","DOI":"10.31209\/2019.100000110"},{"key":"3","doi-asserted-by":"publisher","DOI":"10.1016\/j.future.2018.04.064"},{"issue":"3","key":"4","first-page":"755","volume":"20","year":"2019","journal-title":"Journal of Internet Technology"},{"key":"5","doi-asserted-by":"publisher","DOI":"10.1109\/tbme.2010.2099226"},{"key":"6","doi-asserted-by":"publisher","DOI":"10.1109\/access.2018.2807700"},{"issue":"3","key":"7","first-page":"273","volume":"20","year":"1995","journal-title":"Machine Learning"},{"key":"9","doi-asserted-by":"publisher","DOI":"10.1109\/tnsre.2017.2748388"},{"key":"10","doi-asserted-by":"publisher","DOI":"10.1109\/tnsre.2019.2904708"},{"key":"11","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2011.02.110"},{"key":"12","doi-asserted-by":"publisher","DOI":"10.1109\/tcyb.2014.2334595"},{"key":"13","doi-asserted-by":"publisher","DOI":"10.1126\/science.1136800"},{"key":"16","doi-asserted-by":"publisher","DOI":"10.1007\/s13042-016-0532-0"},{"key":"17","doi-asserted-by":"publisher","DOI":"10.1109\/tkde.2012.202"},{"key":"18","doi-asserted-by":"publisher","DOI":"10.1016\/j.clinph.2008.02.001"},{"key":"27","doi-asserted-by":"publisher","DOI":"10.1109\/tkde.2014.2310215"},{"key":"28","first-page":"161","volume":"5","year":"2009","journal-title":"Journal of Machine Learning Research\u2014Proceedings Track"},{"key":"29","doi-asserted-by":"publisher","DOI":"10.1007\/s10115-016-0996-y"},{"key":"30","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2016.02.054"},{"key":"31","doi-asserted-by":"publisher","DOI":"10.1109\/tkde.2003.1198387"},{"key":"32","doi-asserted-by":"publisher","DOI":"10.1145\/1217299.1217303"},{"key":"33","doi-asserted-by":"publisher","DOI":"10.1109\/tfuzz.2016.2637405"},{"key":"34","doi-asserted-by":"publisher","DOI":"10.1109\/tcyb.2014.2330844"}],"container-title":["Computational and Mathematical Methods in Medicine"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/downloads.hindawi.com\/journals\/cmmm\/2020\/4147807.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/downloads.hindawi.com\/journals\/cmmm\/2020\/4147807.xml","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/downloads.hindawi.com\/journals\/cmmm\/2020\/4147807.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,5,8]],"date-time":"2020-05-08T19:30:58Z","timestamp":1588966258000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.hindawi.com\/journals\/cmmm\/2020\/4147807\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,5,8]]},"references-count":23,"alternative-id":["4147807","4147807"],"URL":"https:\/\/doi.org\/10.1155\/2020\/4147807","relation":{},"ISSN":["1748-670X","1748-6718"],"issn-type":[{"type":"print","value":"1748-670X"},{"type":"electronic","value":"1748-6718"}],"subject":[],"published":{"date-parts":[[2020,5,8]]}}}